Video signature extraction device

ABSTRACT

A video signature extraction device includes an each-picture feature extraction unit which extracts a feature of each picture, which is a frame or a field, as an each-picture visual feature from an input video; a time axial direction change region extraction unit which analyzes an image change in a time direction with respect to predetermined regions in a picture from the video, obtains a region having a large image change, and generates change region information which is information designating the region; an each-region feature extraction unit which extracts a feature of the region corresponding to the change region information as an each-region visual feature from the video; and a multiplexing unit which multiplexes the each-picture visual feature, the each-region visual feature, and the change region information, and generates a video signature.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a Divisional of U.S. patent application Ser. No.13/056,773, filed Jan. 31, 2011, which is a National Stage ofInternational Application No. PCT/JP2010/000278, filed Jan. 20, 2010,claiming priority based on Japanese Patent Application No. 2009-012815,filed Jan. 23, 2009, the contents of all of which are incorporatedherein by reference in their entirety.

TECHNICAL FIELD

The present invention relates to video signature extraction devices,video signature extraction methods, and video signature extractionprograms, for retrieving videos, which are capable of detecting similaror identical moving image segments among a plurality of moving images.

BACKGROUND ART

An exemplary device for extracting and matching features of movingimages is described in Non-Patent Document 1. FIG. 14 is a block diagramshowing the device described in Non-Patent Document 1.

A block unit feature extraction unit 1000 extracts features in blockunits from a first video to be input, and outputs a first feature to amatching unit 1030. Another block unit feature extraction unit 1010extracts features in block units from a second video to be input, andoutputs a second feature to the matching unit 1030. A weightingcoefficient calculation unit 1020 calculates a weighting value of eachof the blocks based on a learning video to be input, and outputs aweighting coefficient to the matching unit 1030. The matching unit 1030compares the first feature output from the block unit feature extractionunit 1000 with the second feature output from the block unit featureextraction unit 1010 using the weighting coefficient output from theweighting coefficient calculation unit 1020, and outputs a matchingresult.

Next, operation of the device shown in FIG. 14 will be described.

The block unit feature extraction unit 1000 divides each of the framesof the input first video into blocks, and calculates a feature foridentifying the video from each block. Specifically, the block unitfeature extraction unit 1000 determines the type of the edge for eachblock, and calculates the type as a feature of each block. Then, foreach of the frames, the block unit feature extraction unit 1000 forms afeature vector configured of the edge types of the respective blocks.Then, the block unit feature extraction unit 1000 calculates the featurevector of each of the frames, and outputs the acquired feature to thematching unit 1030 as the first feature.

Operation of the block unit feature extraction unit 1010 is similar tothat of the block unit feature extraction unit 1000. The block unitfeature extraction unit 1010 calculates the second feature from theinput second video, and outputs the acquired second feature to thematching unit 1030.

On the other hand, the weighting coefficient calculation unit 1020calculates probability that a caption is inserted in each block of aframe beforehand, using a learning video. Then, based on the calculatedprobability, the weighting coefficient calculation unit 1020 calculatesa weighting coefficient of each block. Specifically, a weightingcoefficient is calculated such that weighting becomes high as theprobability of a caption being superposed is low, in order to improverobustness to caption superposition. The acquired weighting coefficientis output to the matching unit 1030.

The matching unit 1030 compares the first feature output from the blockunit feature extraction unit 1000 with the second feature output fromthe block unit feature extraction unit 1010, using the weightingcoefficient output from the weighting coefficient calculation unit 1020.Specifically, the matching unit 1030 compares the features of the blocksat the same position in the two frames, and calculates a score of theblock unit such that the score is 1 if they are the same, and the scoreis 0 if they are not the same. The matching unit 1030 sums the acquiredscores of the block units by weighting them with use of the weightingcoefficients, and calculates a matching score (similarity of a frameunit) of the frame. The matching unit 1030 performs these processes onthe respective frames to thereby acquire a matching result between thefirst video and the second video.

Through these processes, it is possible to perform matching of movingimages while reducing influences of caption superposition in portionswhere the influences may be large, and to achieve high matching accuracyeven with caption superposition.

Patent Document 1 describes a device for retrieving moving images, usingfeatures of images such as mean values in block units or DCTcoefficients and motion vector information obtained between previous andnext frames. In the moving image retrieval device of Patent Document 1,first, at least one of values of physical moving image featureinformation including luminance, color difference information, and colorinformation of each frame, a mean value thereof, the sum of the values,or a difference value thereof, is extracted from the input image withrespect to each frame. Then, the extracted values are aligned on a timeaxis, and all values in the alignment or values extracted from thealignment in certain intervals or irregular intervals are extracted asmoving image feature information. Alternatively, it is also possible toextract a DCT coefficient and motion compensation information of a framefrom compressed moving image data, and obtain a mean value of DCTcoefficients, a sum value thereof, or a difference value of the values,and from the motion compensation information, obtain at least one of amotion vector, an average motion vector between previous and nextframes, a sum motion vector, a difference vector, a motion vector of theframe as a whole, and the like. Then, the obtained values are aligned ona time axis, and all values in the alignment or values extracted fromthe alignment in certain intervals or irregular intervals are extractedas moving image feature information.

PRIOR ART DOCUMENTS Patent Document

-   Patent Document 1: Japanese Unexamined Patent Publication No.    2000-194727

Non-Patent Documents

-   Non-Patent Document 1: Kota Iwamoto, Eiji Kasutani, Akio Yamada,    “Image Signature Robust to Caption Superimposition for Video    Sequence Identification”, Proceedings of International Conference on    Image Processing (ICIP2006), 2006-   Non-Patent Document 2: Eiji Kasutani, Ryoma Oami, Akio Yamada,    Takami Sato, and Kyoji Hirata, “Video Material Archive System for    Efficient Video Editing Based on Media Identification”, Proceedings    of International Conference on Multimedia and Expo (ICME2004), pp.    727-730, 2004

SUMMARY OF THE INVENTION Problems to be Solved by the Invention

A problem involved in the above art is that it is difficult to improvethe discrimination accuracy in a time direction in scenes having lesstemporal changes. In the case of Non-Patent Document 1, as the weightingat the time of matching is determined by the probability of captionsuperposition, control is not focused on matching of scenes having lesstemporal changes. In scenes having less temporal changes, it is oftenthe case that the screen image seldom moves, and that changes in theimage such as motion and brightness changes are caused only in a localarea. In order to improve the discrimination accuracy in that case,although it is only necessary to extract features in more detail,including extracting features in block units, this causes a problem ofan increase in the feature size. Even in the case of Patent Document 1,although motion information is used and so motion is taken into accountin features, features obtained from motion information and featuresobtained from luminance values and DCT coefficients are used independentfrom each other. As such, if extraction is performed to a more detailedlevel, a problem of an increase in the feature size, which is the sameas that involved in Non-Patent Document 1, will also be caused.

Object of the Invention

An object of the present invention is to provide a video signatureextraction device capable of solving a problem of low discriminationcapability of video signatures generated from moving images having lesstemporal changes.

Means for Solving the Problems

A video signature extraction device, according to an aspect of thepresent invention, includes an each-picture feature extraction unitwhich extracts a feature of each picture, which is a frame or a field,as an each-picture visual feature from an input video; a time axialdirection change region extraction unit which analyzes an image changein a time direction with respect to predetermined regions in a picturefrom the video, obtains a region having a large image change, andgenerates change region information which is information designating theregion; an each-region feature extraction unit which extracts a featureof the region corresponding to the change region information as aneach-region visual feature from the video; and a multiplexing unit whichmultiplexes the each-picture visual feature, the each-region visualfeature, and the change region information, and generates a videosignature.

Effects of the Invention

As the present invention is configured as described above, the presentinvention is able to achieve an advantageous effect of improving thediscrimination accuracy in a time direction even in scenes having lesstemporal changes.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a region diagram showing a first embodiment of an imagesignature extraction device according to the present invention.

FIG. 2 is a block diagram showing an exemplary configuration of a timeaxial direction change region extraction unit 100.

FIG. 3 is an illustration for explaining an exemplary process performedby a change region extraction unit 410.

FIG. 4 is an illustration showing a case where a plurality ofpredetermined regions in a picture are blocks.

FIG. 5 is an illustration showing a case where a plurality ofpredetermined regions in a picture are local regions in differentshapes.

FIG. 6 is a block diagram showing another exemplary configuration of thetime axial direction change region extraction unit 100.

FIG. 7 is an illustration for explaining an exemplary process performedby a change region extraction unit 510.

FIG. 8 is a block diagram showing an exemplary configuration of a videosignature matching device for matching video signatures generated by thevideo signature extraction device of the first embodiment.

FIG. 9 is an illustration for explaining a matching process of twovideos.

FIG. 10 is an illustration for explaining a process performed by aregion matching unit 230.

FIG. 11 is a block diagram showing a second embodiment of a videosignature extraction device according to the present invention.

FIG. 12 is a block diagram showing an exemplary configuration of a videosignature matching device for matching video signatures generated by thevideo signature extraction device of the second embodiment.

FIG. 13 is an illustration showing an example of a feature.

FIG. 14 is a block diagram for explaining related art of the presentinvention.

DESCRIPTION OF EMBODIMENTS

Next, best modes for carrying out the invention will be described indetail with reference to the drawings.

Referring to FIG. 1 showing an image signature extraction deviceaccording to a first embodiment of the present invention, the imagesignature extraction device includes a time axial direction changeregion extraction unit 100, an each-region feature extraction unit 110,an each-picture feature extraction unit 130, and a multiplexing unit120.

The each-picture feature extraction unit 130 extracts an each-picturefeature from an input video, and outputs it to the multiplexing unit120. The time axial direction change region extraction unit 100 obtainschange region information from the video, and outputs it to theeach-region feature extraction unit 110 and to the multiplexing unit120. The each-region feature extraction unit 110 extracts an each-regionvisual feature from the video based on the change region informationoutput from the time axial direction change region extraction unit 100,and outputs it to the multiplexing unit 120. The multiplexing unit 120multiplexes the each-picture visual feature output from the each-picturefeature extraction unit 130, the change region information output fromthe time axial direction change region extraction unit 100, and theeach-region visual feature output from the each-region featureextraction unit 110, and generates and outputs a video signature.

It should be noted that the video signature extraction device of thepresent embodiment can be realized by a computer in the followingmanner, for example. A disk or a semiconductor memory, storing programsfor allowing a computer to function as the video signature extractiondevice is prepared, and the computer is caused to read the program. Thecomputer controls the operation of itself according to the readoutprogram to thereby realize the time axial direction change regionextraction unit 100, the each-region feature extraction unit 110, themultiplexing unit 120, and the each-picture feature extraction unit 130on the self computer.

Next, operation of the first embodiment shown in FIG. 1 will bedescribed in detail.

First, a video is input to the each-picture feature extraction unit 130.If the original video is coded, the video is first decoded by a decoder,and then the data is input in picture units composed of frames orfields.

The each-picture feature extraction unit 130 calculates a feature vectorof each picture. The each-picture feature extraction unit 130 considersa picture as one still image, and extracts a vector of a visual featureindicating features such as colors, patterns, shapes, and the like ofthis picture. As the feature, it is possible to use a feature vectorwhich is obtained by calculating a difference between features ofregions with respect to a pair of local regions corresponding to eachdimension of the feature vector (for example, calculating a mean valueof pixel value within a region with respect to each region of a pair ofregions and obtaining a difference in mean values between regions), andusing a quantized value obtained by quantizing the difference as a valueof each dimension. The feature vector, calculated for each picture, isoutput to the multiplexing unit 120 as an each-picture visual feature.

Further, the video is also input to the time axial direction changeregion extraction unit 100. In the time axial direction change regionextraction unit 100, an amount of change of the image in a timedirection is calculated. An amount of change in each of thepredetermined regions in the picture is calculated using a currenttarget picture and the previous and next pictures. Then, a region wherethe amount of change is relatively large in the screen image isobtained. Regions for obtaining the amounts of change are formed bydividing a picture. The regions may be a plurality of blocks as shown inFIG. 4, or a plurality of local regions having different shapes as shownin FIG. 5. Further, the shape of the blocks is not limited to rectangle.As a region having a larger change in a time direction has a largerpossibility of contributing to discrimination of a video, a plurality ofregions are selected in order in which a region having a largest amountof change is the first. Selection may be performed by selecting acertain number of regions in descending order, or selecting regions inwhich the amount of change is a threshold or larger. The details ofcalculating the amount of change will be described below. Informationfor specifying the selected regions such as index information of theselected regions is output as change region information. For example, ina scene where an anchor person speaks in a news program, there is a casewhere no motion is generated in areas other than an area around the faceof the anchor person. In that case, as a change in a time direction inthe region corresponding to the face of the anchor person becomesrelatively larger than changes in other regions in the screen image,information designating the region corresponding to the face is outputas change region information.

It should be noted that the change region information may be calculatedfor each picture, or calculated for several pictures in a lump, andoutput. For example, if a portion with motion within a shot is limitedto a particular region, it is possible to calculate and output changeregion information which is common to the entire shot. Morespecifically, it is possible that change region information, obtainedfor one picture within a shot, is also used for another picture in theshot. It is also possible to calculate time axial direction changes forall or a plurality of pictures within a shot and, with use of arepresentative value thereof (mean, median, or the like), obtain anddescribe change region information for the entire shot and use it forall pictures within the shot.

However, units for outputting change region information are not limitedto shots, and change region information may be output in fixed timeintervals such as every several pictures. It is also possible tocalculate a time segment, to which the same change region information isapplicable, from the amount of change in a time direction, and calculateand output the change region information in a lump with respect to thepictures included in the time segment. In that case, as the number ofpictures put together varies each time, the number of pictures is alsodescribed together. A time segment to which the same change regioninformation is applicable is able to be calculated by applying thresholdprocessing on variation of the amount of change in the time directionbetween pictures. As such, an amount of change in the time axialdirection in the head picture in a time segment and an amount of changein the time axial direction in the current picture are compared, and ifthe degree of change exceeds a threshold, a segment up to the previouspicture is considered as one group, whereby change region informationwith respect to the segment is calculated. The change region informationwith respect to that segment may be used as change region information ofany picture in the segment or a representative value of change regioninformation of the pictures in the segment. Through these processes,regardless of a processing target video, the amount of information ofthe change region information can be reduced while keeping highdescrimination accuracy in the time direction.

The change region information calculated as described above is output tothe each-region feature extraction unit 110 and to the multiplexing unit120.

The each-region feature extraction unit 110 extracts a feature in aregion unit with respect to a region specified by the change regioninformation output from the time axial direction change regionextraction unit 100. In this process, the feature in a region unit maybe the same as, or different from, the feature of the entire screenimage calculated by the each-picture feature extraction unit 130. Forexample, it is possible to use a feature in which, with respect to theabove-described pair of local regions corresponding to each dimension ofthe feature vector, a feature difference between the regions iscalculated and used as each dimensional value of the feature vector. Thefeature of the region designated by the change region information isoutput to the multiplexing unit 120 as an each-region visual feature.

The multiplexing unit 120 multiplexes the each-picture visual featureoutput from the each-picture feature extraction unit 130, theeach-region visual feature output from the each-picture featureextraction unit 110, and the change region information output from thetime axial direction change region extraction unit 100, and generatesand outputs a video signature. In this embodiment, the multiplexing unit120 generates a video signature by multiplexing them in such a mannerthat these pieces of information can be separated at the time ofmatching. As multiplexing methods, it is possible to multiplex threepieces of information for each picture by interleaving them, orseparately put together each of the each-picture visual feature, theeach-region visual feature, and the change region information andfinally connect them to thereby multiplex them, or multiplex theeach-picture visual feature, the each-region visual feature, and thechange region information for each predetermined segment (for example,by a time segment unit for calculating change region information).

Next, an embodiment of the time axial direction change region extractionunit 100 will be described with reference to FIG. 2.

Referring to FIG. 2 showing an embodiment of the time axial directionchange region extraction unit 100, the time axial direction changeregion extraction unit 100 includes an inter-picture differencecalculation unit 400 and a change region extraction unit 410.

The inter-picture difference calculation unit 400 calculatesinter-picture difference information from the input video, and outputsit to the change region extraction unit 410. The change regionextraction unit 410 calculates change region information using theinter-picture difference information output from the inter-picturedifference calculation unit 400 and a feature extraction parameter(information describing each dimension of the feature and the extractiontarget region), and outputs it.

Next, operation of the time axial direction change region extractionunit 100 shown in FIG. 2 will be described.

First, a video is input to the inter-picture difference calculation unit400. The inter-picture difference calculation unit 400 calculates adifference in pixel value between pictures. Calculation of a differencemay be performed for each pixel unit or performed for a region for whichcalculation for some pixels can be made at once (for example, a block).For example, a method in which a representative value (mean, median,etc.) with respect to each region is obtained beforehand, and then, adifference with a representative value of a region at the same locationis obtained between pictures. Further, a difference between pixel valuesmay be a difference between luminance values. It is also possible to usecolor components of R, G, and B as pixel values, and calculate adifference of at least one of them to use as a difference of the pixelvalue. Of course, a color space may be any color space such as HSV orL*a*b*, rather than RGB. Further, as a difference, it is possible toobtain an absolute value of a difference by performing absolute valuecomputation, rather than simply subtracting a pixel value. Thecalculated difference data between the pictures is output to the changeregion extraction unit 410 as inter-picture difference information.

The change region extraction unit 410 calculates difference informationof each region from the inter-picture difference information. In orderto do so, first, in the processing target picture, a value to beincremented in a region corresponding to a moving object is calculated.This is achieved by obtaining a product of a difference value betweenthe processing target picture and the previous picture, and a differencevalue between the processing target picture and the next picture.

This is shown in FIG. 3. In FIG. 3, a T picture represents a processingtarget picture, a T−1 picture represents the previous picture, and a T+1picture represents the next picture. In these pictures, it is assumedthat a rectangle shaded object remains stationary, and only a roundblack object moves. In this case, the inter-picture differencecalculation unit 400 has calculated a difference between the processingtarget T picture and the previous T−1 picture. In this case, adifference is only generated by the movement of the round object, asshown in FIG. 3. However, the difference value itself tends to becomelarger at both location of the round object in the T picture andlocation of the object in the T−1 picture. Similarly, a differencebetween the next T+1 picture and the T picture becomes larger at bothlocation of the round object in the T picture and location of the roundobject in the T+1 picture. Then, a product of both difference images iscalculated. As it is only the position of the round object in the Tpicture where the difference value becomes larger in both differenceimages, it is possible to increase only the difference in the movingobject region in the T picture. Although a method of calculation usingthe previous and next pictures of the processing target picture has beendescribed in this embodiment, calculation can also be performed in thesame manner using pictures of a few pictures before and a few picturesafter. As such, it is possible to increase only the difference in themoving object region in the same manner using a T−m picture and a T+npicture. By collecting the results obtained in this way by each region,the amount of change in the region is calculated.

More specifically, the amount of change in a region is calculatedaccording to the following Expression 1.

$\begin{matrix}{{w(i)} = {\sum\limits_{x \in {R{(i)}}}^{\;}\; {{{{f_{T - 1}(x)} - {f_{T}(x)}}}{{{f_{T + 1}(x)} - {f_{T}(x)}}}}}} & \left\lbrack {{Expression}\mspace{14mu} 1} \right\rbrack\end{matrix}$

In Expression 1, f_(T)(x) represents a pixel value at a position x ofthe T picture, R(i) represents the i^(th) region (a group of pixels),and w(i) represents the amount of change in the i^(th) region. Althoughsimple addition in a region is used in this embodiment, it is alsopossible to calculate the amount of change in a region by obtaining anaverage within a region, using a square for addition, or using anotherstatistic such as a median or a maximum value. Further, it is alsopossible to calculate the amount of change by not using the values ofall pixels in a region. For example, the amount of change can becalculated by using every other pixel.

Based on the amounts of change with respect to respective regionscalculated in this manner, a region having a large amount of change isobtained. Specifically, it is possible to calculate regions in which theamount of change exceeds a certain threshold, or select a certain numberof regions in descending order of amount of change. Then, informationdescribing the selected regions (e.g., indexes of regions) is output aschange region information. For example, in the case where the regionsdefined on the picture are blocks obtained by dividing the screen imageinto sixteen pieces as shown in FIG. 4 and the amount of changeincreases in the shaded blocks, the indexes 6, 10, and 12, of the blocksare output as change region information. Further, in the case where theregions defined on the picture are a plurality of local regions inrandom shapes as shown in FIG. 5 and the amount of change increases inthe shaded local region, the index 2 of the local region is output aschange region information.

Further, the change region information is not necessary calculated forall pictures, and may be calculated for every other picture. In thatcase, it is possible to sum the amounts of change with respect to theregions calculated in a plurality of pictures to obtain change regioninformation corresponding to the pictures.

If the feature in the entire image largely changes temporality, as it ispossible to perform matching without features in region units, it is notnecessary to calculate a feature of each region (block or local region)with respect to such a video or a video segment. For example, if thenumber of regions having small amount of change in a time axialdirection is not more than a certain threshold, a feature is notcalculated for each block or local region. Specifically, nothing isoutput as change region information, or change region informationincludes information indicating that there is no feature extractiontarget region.

Thereby, it is possible to avoid calculating unnecessary region featuresso as to prevent the size of video features from being increased to anunnecessary level, whereby features can be calculated only fromnecessary portions.

As the time axial direction change region extraction unit 100 shown inFIG. 2 is only necessary to obtain a difference between picturesbasically, a processing load can be suppressed.

Next, another embodiment of the time axial direction change regionextraction unit 100 will be described with reference to FIG. 6.

Referring to FIG. 6 showing another embodiment of the time axialdirection change region extraction unit 100, the time axial directionchange region extraction unit 100 includes a motion informationcalculation unit 500 and a change region extraction unit 510.

The motion information calculation unit 500 receives a video, calculatesa motion vector, and outputs motion vector information to the changeregion extraction unit 510. The change region extraction unit 510calculates change region information using the motion vector informationoutput from the motion information calculation unit 500 and a featureextraction parameter, and outputs it.

Next, operation of the time axial direction change region extractionunit 100 shown in FIG. 6 will be described.

First, a video is input to the motion information calculation unit 500.The motion information calculation unit 500 performs motion estimationbetween the current target picture and the previous (or next) picture tocalculate a motion vector. As a method of calculation a motion vector,any vector estimation methods including a method based on a conventionalgradient method and a method based on a block matching method may beused. Further, motion may be calculated in pixel units, or it is alsopossible to divide an image into a plurality of small regions and motionmay be calculated for the small region units. Information describing thelocation of the motion vector calculated in this manner is output asmotion vector information. The motion vector information may beinformation directly describing each motion vector calculated within thepicture, or information describing motion only in a region where amotion vector other than 0 is calculated, together with informationspecifying the region. The calculated motion vector describinginformation is output to the change region extraction unit 510.

The change region extraction unit 510 collects the calculated motionvectors for each region, and calculates the amount of motion within theregion.

This is shown in FIG. 7. FIG. 7 shows the states of the T picture andthe T−1 picture. By performing motion estimation processing on thesepictures, a motion vector is calculated in a portion corresponding tothe motion of the round object. Although the case of using animmediately previous picture has been described in this example, it ispossible to perform motion estimation processing using a picture of somepictures ago or some pictures after. Further, it is also possible toperform motion estimation processing using a several number of pictures,rather than using only two pictures. Even in that case, a motion pictureis also calculated in a portion with motion. By using this motionvector, the amount of motion within each region is calculated. Forexample, the sum of the lengths of the motion vectors is calculatedwithin a region, which is represented by Expression 2.

$\begin{matrix}{{w(i)} = {\sum\limits_{x \in {R{(i)}}}^{\;}\; {{v(x)}}}} & \left\lbrack {{Expression}\mspace{14mu} 2} \right\rbrack\end{matrix}$

In Expression 2, v(x) represents a motion vector at x. The other signsare the same as those used in Expression 1. Although simple addition ina region is used in this embodiment, it is also possible to obtain arepresentative amount of motion in a region by obtaining an averagewithin a region, using a square for addition, or using another statisticsuch as a median or a maximum value. Further, it is also possible tocalculate the amount of motion by not using the all motion vectors in aregion. For example, the amount of motion can be calculated by thinningappropriately.

As the time axial direction change region extraction unit 100 shown inFIG. 6 calculates motion, the amount of processing increases in general,compared with the case shown in FIG. 2. However, as actual motion iscalculated, a region having motion in a time direction can be obtainedwith higher accuracy, compared with the case shown in FIG. 2.

Next, an embodiment of the video signature matching device of thepresent invention will be described.

Referring to FIG. 8 showing an embodiment of the video signaturematching device, the video signature matching device includes ademultiplexing unit 200, another demultiplexing unit 210, a picturematching unit 220, a region matching unit 230, and a matching resultdetermination unit 240. It should be noted that this embodiment of thevideo signature matching device can be realized by a computer which iscontrollable by programs.

The demultiplexing unit 200 demultiplexes an input first videosignature, and outputs a first each-picture visual feature to thepicture matching unit 220 and outputs a first each-region visual featureand first change region information to the region matching unit 230.Similarly, the demultiplexing unit 210 also demultiplexes an inputsecond video signature, and outputs a second each-picture visual featureto the picture matching unit 220 and outputs a second each-region visualfeature and second change region information to the region matching unit230. The picture matching unit 220 compares the first each-picturevisual feature output from the demultiplexing unit 220 with the secondeach-picture visual feature output from the demultiplexing unit 210, andoutputs a picture matching result to the matching result determinationunit 240, and also outputs region matching execution information to theregion matching unit 230. Based on the region matching executioninformation output from the picture matching unit 220, the first changeregion information output from the demultiplexing unit 200, and thesecond change region information output from the demultiplexing unit210, the region matching unit 230 compares the first each-region visualfeature output from the demultiplexing unit 200 with the secondeach-region visual feature output from the demultiplexing unit 210, andoutputs a region matching result to the matching result determinationunit 240. The matching result determination unit 240 calculates amatching result from the picture matching result output from the picturematching unit 220 and the region matching result output from the regionmatching unit 230, and outputs it.

Next, operation of the embodiment of the video signature matching deviceaccording to the present invention shown in FIG. 8 will be described.

The first video signature is input to the demultiplexing unit 200. Thedemultiplexing unit 200 separates the first each-picture visual feature,the first each-region visual feature, and the first change regioninformation, from the first video signature. In this process, separationis performed by means of a separation method corresponding to the methodused for multiplexing by the multiplexing unit 120. The firsteach-picture visual feature generated by separation is output to thepicture matching unit 220, and the first each-region feature and thefirst change region information are output to the region matching unit230.

The second video signature is input to the demultiplexing unit 210.Operation of the demultiplexing unit 210 is the same as that of thedemultiplexing unit 200, and the second each-picture visual featuregenerated by separation is output to the picture matching unit 220, andthe second each-region feature and the second change region informationare output to the region matching unit 230.

The picture matching unit 220 compares the first each-picture visualfeature output from the demultiplexing unit 200 with the secondeach-picture visual feature output from the demultiplexing unit 210.They may be compared using the degree of similarity indicatingsimilarity of both features, or using a distance indicating the level ofdifference between both features. In the case of comparing them using adistance, comparison will be performed according to Expression 3.

$\begin{matrix}{d = {\sum\limits_{i = 1}^{N\;}\; {{{v_{1}(i)} - {v_{2}(i)}}}}} & \left\lbrack {{Expression}\mspace{14mu} 3} \right\rbrack\end{matrix}$

It should be noted that N represents the number of dimensions of thefeature, and v₁(i) and v₂(i) respectively represent values of the i^(th)dimension of the first and second each-picture visual features. Byperforming comparison in picture units and summing, specific segments ofthe first video and the second video are compared. For example, a numberof pairs of pictures having distance values not more that a threshold isobtained in a comparison in picture units, and if the value issufficiently large relative to the number of pictures included in thesegment, the both videos are determined to be of the same segment, whileif not, they are determined not to be of the same segment. By performingthis process on combinations in arbitrary segments of the first videoand the second video, all of the same segments of random length includedin these videos can be determined. Instead of performing thresholdprocessing on distances in picture units, it is also possible to performdetermination according to whether or not a value obtained by summingthe distances within a segment is smaller than a predeterminedthreshold. Of course, a mean value may be obtained, rather than a totalvalue. Alternatively, comparison may be performed in a segment whileeliminating outlier. Such comparison may be performed using a median ora result of M assumption, instead of a mean value, for example.

As a method of comparing segments of any length, the matching methoddescribed in Non-Patent Document 2 can also be used. As shown in FIG. 9,for matching between videos, a matching window having a length of Lpictures is provided, and the window is caused to slide on the firstvideo and the second video respectively, and they are compared with eachother. If the segments within the matching windows are determined to beidentical, the matching window is extended by a length of p pictures soas to continue the matching process. As long as both segments aredetermined to be identical, the process of extending the matching windowby p pictures is repeated so as to obtain the identical segments withthe maximum length. Thereby, the identical segments with the maximumlength, in the compared segments, can be acquired effectively.

It should be noted that although the case of using a distance as ameasure has been described above, comparison can also be performed usingthe degree of similarity. In that case, comparison is specificallyperformed using the degree of similarity S calculated by Expression 4.

$\begin{matrix}{S = {\sum\limits_{i = 1}^{N\;}{{Sim}\; \left( {{v_{1}(i)},{v_{2}(i)}} \right)}}} & \left\lbrack {{Expression}\mspace{14mu} 4} \right\rbrack\end{matrix}$

Sim(x, y) is a function showing similarity between x and y, and thevalue becomes larger as the values of x and y are more similar. Forexample, if the distance between x and y is d(x, y), a function shown asExpression 5 can be used.

$\begin{matrix}{{{Sim}\; \left( {x,y} \right)} = \frac{1}{1 + {d\; \left( {x,y} \right)}}} & \left\lbrack {{Expression}\mspace{14mu} 5} \right\rbrack\end{matrix}$

Alternatively, Sim(x, y) may be a function that returns 1 when x and ymatch, and returns 0 otherwise, as Kronecker delta. Alternatively, if anangle (cosine value) between feature vectors is used as a degree ofsimilarity, comparison is performed based on the degree of similarity Scalculated by Expression 6.

$\begin{matrix}{S = \frac{\sum\limits_{i = 1}^{N\;}{{v_{1}(i)}{v_{2}(i)}}}{\sum\limits_{i = 1}^{N\;}{{v_{1}(i)}^{2}{\sum\limits_{i = 1}^{N\;}{v_{2}(i)}^{2}}}}} & \left\lbrack {{Expression}\mspace{14mu} 6} \right\rbrack\end{matrix}$

By using the degree of similarity acquired as described above, matchingcan be performed in a similar manner to that of the case of distance.

Then, a matching result is output to the matching result determinationunit 240. A matching result includes information specifying identicalsegments, such as picture numbers and time information of the identicalsegments. On the other hand, if there is no identical segment,information indicating such a fact is included. It is also possible thata case where nothing is included in a matching result corresponds to thecase where no identical segment is present.

When matching is performed in this manner, there is a case where a videosegment having less motion in a time direction corresponds to not onlyone segment, but to a plurality of segments of another video (includinga case of matching any partial section in a series of segments). Even ifa segment corresponds to one segment, there is a case where a pluralityof matching candidate segments exist substantially, because there is nota large difference in distance value or degree of similarity with othercandidate segments. In that case, as sufficient matching was not able tobe performed in the each-picture matching, region matching executioninformation notifying execution of region matching is output to theregion matching unit 230. In contrast, if there is no segment which canbe determined to match, or if there is a large difference between thedistance value or the degree of similarity of the segments which weredetermined to match and the distance value or the degree of similarityof other candidate segments, it is determined that matching for eachregion is not necessary, so that region matching execution informationwill not be output.

The region matching unit 230 compares the first each-region visualfeature output from the demultiplexing unit 200 with the secondeach-region visual feature output from the demultiplexing unit 210,based on the first change region information output from thedemultiplexing unit 200 and the second change region information outputfrom the demultiplexing unit 210. However, this matching is performedaccording to the region matching execution information output from thepicture matching unit 220. This means that if region matching executioninformation is not output, matching is not performed, and a regionmatching result is not output. When region matching executioninformation is output, region matching is performed. The region matchingexecution information also includes information specifying target videosegments, that is, information regarding target segments which were notable to be narrowed down in the picture matching, and region matching isperformed on those segments.

When performing matching, pieces of change region information arecompared to check whether there are regions located at the sameposition. If there are no regions located at the same position, regionmatching is not performed. On the other hand, if there is at least oneregion located as the same position, each-region matching is performedon such a region. A matching method in region units is the same as thecase of performing matching on the entire screen. As such, a distancebetween features is calculated, and if the distance is not larger than acertain threshold, the regions are determined to match each other.Alternatively, it is possible to use a degree of similarity betweenfeatures, instead of a distance, and if the degree of similarity islarger than a certain threshold, the regions are determined to matcheach other. If there are a plurality of regions at the same position,matching is respectively performed on all of the regions. For example,in the case where change region information of one video designates ablock in FIG. 4 and change region information of another videodesignates a block in FIG. 10, the positions of the blocks havingindexes 6 and 10 are the same in both cases. As such, matching isperformed on the blocks 6 and 10 to determine whether they match eachother.

Similar to the case of matching between pictures, the above-describedmatching process is performed on regions with respect to a pictureincluded in certain segments, and checks whether the segments match eachother. In this process, although there may be a picture which cannot becompared due to inconsistency in the change region information, matchingbetween regions is performed by eliminating such a picture fromevaluation. For example, among a T picture, a T+1 picture, and a T+2picture, if matching can be performed between the T picture and the T+2picture but cannot be performed on the T+1 picture, only a resultobtained from the T picture and the T+2 is used for determination.

Then, in the region matching process, a matching result includingsegments determined to match is output to the matching resultdetermination unit 240 as a region matching result.

The matching result determination unit 240 determines and outputs afinal matching result, based on the picture matching result output fromthe picture matching unit 220 and the region matching result output fromthe region matching unit 230. If there is only a picture matchingresult, determination is made from the picture matching result. If thereare both picture matching result and region matching result, the bothresults are compared, and a matched segment included in both the picturematching result and the region matching result is output. If the regionmatching result does not include any matching segment because matchingwas not performed due to inconsistency in change region information, thepicture matching result is directly output.

The description of the embodiment of the video signature matching deviceaccording to the present invention ends.

Effects of First Embodiment

According to the present embodiment, even in the case where a change ina time direction is small in the screen image as a whole and it isdifficult to accurately perform position matching in the time direction,matching accuracy in the time direction can be improved by obtaininglocal change information and describing it compactly so as to reduce thesize of the video signature. As such, even in a scene having a poortemporal change, as a feature is calculated independently for a regionwhere changes in the image such as motion or luminous changes occur, itis possible to perform matching with high reliability using regions withmotion.

Further, in the present embodiment, as an inter-picture pixel valuedifference is calculated between a picture for which change regioninformation is calculated and previous and next pictures thereof, andthe change region information is calculated based on the inter-picturepixel value difference, a processing load to calculate the change regioninformation can be reduced.

Further, in the present embodiment, as motion estimation processing isperformed between a picture for which change region information iscalculated and previous and next pictures thereof, and the change regioninformation is calculated based on the estimated degree of the magnitudeof motion, it is possible to obtain a region including motion in a timedirection with high accuracy.

Next, a second embodiment of the present invention will be describedwith reference to the drawings.

Referring to FIG. 11 showing a video signature extraction deviceaccording to the second embodiment of the present invention, the videosignature extraction device includes the time axial direction changeregion extraction unit 100, the each-region feature extraction unit 110,an each-picture feature extraction unit 630, a multiplexing unit 620,and a matching weight information extraction unit 610.

The connection relationship of the time axial direction change regionextraction unit 100 and the each-region feature extraction unit 110 isthe same as that shown in FIG. 1. The each-picture feature extractionunit 630 receives a video and a feature extraction parameter, andoutputs an each-picture visual feature to the multiplexing unit 620. Thematching weight information extraction unit 610 receives a video and afeature extraction parameter, and outputs matching weight information tothe multiplexing unit 620. The multiplexing unit 620 receives changeregion information output from the time axial direction change regionextraction unit 100, an each-feature visual feature output from theeach-region feature extraction unit 110, an each-picture visual featureoutput from the each-picture feature extraction unit 130, and matchingweight information output from the matching weight informationextraction unit 610, and outputs a multiplexed result as a videosignature. It should be noted that the video signature extraction deviceof the present embodiment can be realized by a computer which iscontrollable by programs.

Next, operation of the second embodiment shown in FIG. 11 will bedescribed in detail.

Operation of the time axial direction change region extraction unit 100and operation of the each-region feature extraction unit 110 are thesame as those in the case shown in FIG. 1.

Operation of the each-picture feature extraction unit 630 is alsosimilar to that of the each-picture feature extraction unit 130, exceptfor extracting a feature of each picture in accordance with a featureextraction parameter. However, a visual feature is not a featureobtained by converting the entire image on the screen but a featurecalculated from a partial region within the screen image. As such, it isassumed that each dimension of a feature vector corresponds to aparticular region within the screen image by a feature extractionparameter and that a value of a feature extracted from the region isstored. For example, each dimension of a feature vector is assumed to bea feature extracted from each block formed by dividing the screen imageinto blocks. A value of each dimension of a feature may be obtained froma predetermined region in any shape. Information describing a regionwhich is an extraction target with respect to each dimension of afeature is called a feature parameter. Specifically, if each dimensionof a feature vector is a feature extracted from a particular blockwithin the screen image, information describing the particular block forextracting the feature (coordinate value of the block, index number ofthe block, and the like) serves as a feature parameter. In another case,if a local region in any of a variety of shapes corresponds to eachdimension of a feature vector, information describing the local region(information indicating location, size, and shape of the local region)serves as a feature parameter.

The matching weight information extraction unit 610 calculates an amountof change of the image in a time direction in a region corresponding toeach dimension of the feature by the feature extraction parameter,determines a weighting coefficient of each dimension to be used formatching in accordance with the amount of change, and outputsinformation describing the weighting coefficient as matching weightinformation.

This means that an amount of change is first calculated for each regionusing the current target picture and previous and next pictures. Theamount of change may be an amount of change in a time direction of theimage calculated by means of the method shown in FIG. 3, or an amount ofmotion calculated by means of the method shown in FIG. 7.

Next, according to the amount of change in a time direction calculatedwith respect to each dimension, information describing the degree ofweighting for each dimension of the feature to be used for matching isdetermined. As a region having a larger change in a time direction has ahigher possibility of contributing to discrimination of a video,weighting is performed such that a larger change is determined to bemore important. For example, a degree of weighting may be determined bya function which monotonically increases with respect to an amount ofchange in a time direction. Matching weight information may be acoefficient itself which determines the degree of weighting, or may beinformation of index designating a class among classes formed bydividing the degrees of weighting from low to high. In a scene where ananchor person speaks in a news program, for example, there is a casewhere no motion is found in areas other than an area around the face ofthe anchor person. In that case, as a change in a time direction in thedimension of the region corresponding to the face of the anchor personbecomes relatively larger than changes in other regions in the screenimage, matching weight information, in which weight of the dimension ofthe feature corresponding to the face region (particularly, a regioncorresponding to the mouth and eyes) is high, is calculated.

It should be noted that the matching weight information may becalculated for each picture, or calculated for several pictures in alump, and output. For example, if a portion with motion within a shot islimited to a particular region, it is possible to calculate and outputmatching weight information with respect to the entire shot. Morespecifically, it is possible that matching weight information, obtainedfor one picture in a shot, is also used for other pictures in the shot.Thereby, the amount of calculation of obtaining the matching weightinformation can be reduced, and also, the amount of information of theimage signature can be reduced. Alternatively, it is possible tocalculate matching weight information for all or a plurality of picturesin a shot and, with use of a representative value thereof (mean, median,or the like), describe matching weight of the entire shot and use it forall pictures in the shot. Thereby, the amount of information of thevideo signature can be reduced.

However, units for outputting matching weight information are notlimited to shots, and may be fixed time intervals such as every severalpictures. It is also possible to calculate time segments to which thesame matching weight information is applicable from time directionvariation information, and calculate and output matching weightinformation in a lump with respect to the pictures included in the timesegments. In that case, as the number of pictures put together varieseach time, the number of pictures is also described together. Timesegments to which the same matching weight information is applicable areable to be calculated by applying threshold processing on changes in thetime direction variation information between pictures. As such, timedirection variation information in the head picture in a time segmentand time direction variation information of the current picture arecompared, and if the degree of change exceeds a threshold, a segment upto the previous picture is considered as one unit, whereby matchingweight information with respect to such segment is calculated. Thematching weight information with respect to such segment may be used asmatching weight information of an arbitrary picture in the segment or arepresentative value of matching weight information of the pictures inthe segment. Through these processes, regardless of a processing targetvideo, the amount of information of the matching weight information canbe reduced while keeping high discrimination accuracy in a timedirection.

Further, if a plurality of dimensions of a feature vector correspond tothe same region, they may be shown in a lump as one weight information.For example in the case of Edge Histogram set in ISO/IEC 15938-3, everyfive bins correspond to the same region. In that case, weightinformation may be described in a lump every five bins.

The multiplexing unit 620 multiplexes the change region informationoutput from the time axial direction change region extraction unit 100,the each-region visual feature output from the each-region featureextraction unit 110, the each-picture visual feature output from theeach-picture feature extraction unit 130, and the matching weightinformation output from the matching weight information extraction unit610, and generates and outputs a video signature. The operation of themultiplexing unit 620 is similar to that of the multiplexing unit 120shown in FIG. 1, except for multiplexing the matching weight informationoutput from the matching weight information extraction unit 610.

Next, a matching device according to the second embodiment of thepresent invention will be described.

Referring to FIG. 12 showing a matching device for matching a videosignature generated according to the second embodiment of the presentinvention, the matching device includes a demultiplexing unit 700,another demultiplexing unit 710, a picture matching unit 720, aweighting coefficient calculation unit 730, a region matching unit 230,and a matching result determination unit 240.

The demultiplexing unit 700 demultiplexes an input first videosignature, outputs a first each-picture visual feature to the picturematching unit 720, outputs a first each-region visual feature and firstchange region information to the region matching unit 230, and outputsfirst matching weight information to the weighting coefficientcalculation unit 730. Similarly, the demultiplexing unit 710demultiplexes an input second video signature, outputs a secondeach-picture visual feature to the picture matching unit 720, outputs asecond each-region visual feature and second change region informationto the region matching unit 230, and outputs second matching weightinformation to the weighting coefficient calculation unit 730. Theweighting coefficient calculation unit 730 calculates a weightingcoefficient from the first matching weight information output from thedemultiplexing unit 700 and the second matching weight informationoutput from the demultiplexing unit 710, and outputs the weightingcoefficient to the picture matching unit 720. The picture matching unit720 uses the weighting coefficient output from the weighting coefficientcalculation unit 730 to compare the first each-picture visual featureoutput from the demultiplexing unit 700 with the second each-picturevisual feature output from the demultiplexing unit 710, and outputs apicture matching result to the matching result determination unit 240,and outputs region matching execution information to the region matchingunit 230. Based on the region matching execution information output fromthe picture matching unit 720, the first change region informationoutput from the demultiplexing unit 700, and the second change regioninformation output from the demultiplexing unit 710, the region matchingunit 230 compares the first each-region visual feature output from thedemultiplexing unit 700 with the second each-region visual featureoutput from the demultiplexing unit 710 and outputs a region matchingresult to the matching result determination unit 240. The matchingresult determination unit 240 calculates a matching result from thepicture matching result output from the picture matching unit 720 andthe region matching result output from the region matching unit 230, andoutputs the matching result. It should be noted that the matching deviceof the present embodiment can be realized by a computer which iscontrollable by programs.

Next, operation of the matching device shown in FIG. 12 will bedescribed.

Operation of the demultiplexing unit 700 is almost similar to that ofthe demultiplexing unit 200 shown in FIG. 8, but also separates firstmatching weight information from the first video signature. Similarly,operation of the demultiplexing unit 700 is almost similar to that ofthe demultiplexing unit 210 shown in FIG. 8, but also separates secondmatching weight information from the second video signature. Theseparated first matching weight information and the second matchingweight information are input to the weighting coefficient calculationunit 730.

The weighting coefficient calculation unit 730 calculates a weightingcoefficient with respect to each dimension of the feature, from thefirst matching weight information and the second matching weightinformation. A plurality of methods may be used for calculating aweighting coefficient from the first matching weight information and thesecond matching weight information, if the calculated weightingcoefficient satisfies conditions such that it becomes smaller when bothpieces of matching weight information correspond to a smaller weightvalue and it increases when at least one of weight values correspondingto the matching weight information increases. For example, if respectiveweights calculated from the first matching weight information and thesecond matching weight information are w₁(i) and w₂(i), a weightingcoefficient w(i) is calculated from the following Expression 7.

w(i)=max(w ₁(i),w ₂(i))  [Expression 7]

More generally, the following Expression 8 may be used.

w(i)=|w ₁(i)^(p) +w ₂(i)^(p)|^(1/p)  [Expression 8]

In Expression 8, p represents any natural number, and when p isinfinite, the expression results in Expression 7.

The weight coefficient is calculated for each dimension of the feature,and is output to the picture matching unit 720.

While the operation of the picture matching unit 720 is basicallysimilar to that of the picture matching unit 220 shown in FIG. 8, exceptfor an aspect of using a weight coefficient calculated as describedabove when performing matching between feature vectors.

In that case, the features may be compared using the degree ofsimilarity showing similarity between them, or using a distance showingthe degree of difference between them. In the case of using a distance,comparison is made using a distance d calculated according to Expression9, rather than Expression 3.

$\begin{matrix}{d = {\sum\limits_{i = 1}^{N\;}\; {{w(i)}{{{v_{1}(i)} - {v_{2}(i)}}}}}} & \left\lbrack {{Expression}\mspace{14mu} 9} \right\rbrack\end{matrix}$

In Expression 9, w(i) represents a weight coefficient corresponding tothe i^(th) dimension. Similarly, in the case of using a degree ofsimilarity, Expression 10 and Expression 11 are used, rather thanExpression 4 and Expression 6.

$\begin{matrix}{S = {\sum\limits_{i = 1}^{N\;}{{w(i)}{Sim}\; \left( {{v_{1}(i)},{v_{2}(i)}} \right)}}} & \left\lbrack {{Expression}\mspace{14mu} 10} \right\rbrack \\{S = \frac{\sum\limits_{i = 1}^{N\;}{{w(i)}{v_{1}(i)}{v_{2}(i)}}}{\sum\limits_{i = 1}^{N\;}{{w(i)}{v_{1}(i)}^{2}{\sum\limits_{i = 1}^{N\;}{{w(i)}{v_{2}(i)}^{2}}}}}} & \left\lbrack {{Expression}\mspace{14mu} 11} \right\rbrack\end{matrix}$

Operation of the region matching unit 230 and operation of the matchingresult determination unit 240 are similar to those of the case shown inFIG. 8.

Effects of Second Embodiment

According to the present embodiment, matching accuracy in a timedirection can be improved, compared with the first embodiment. This isbecause by increasing the weight of the feature corresponding to aregion where a change such as motion or a luminance change is caused inthe image, matching is less affected by a feature change due to codingdistortion or the like. For example, it is assumed that a scene in whichan anchor person reads the news in a studio consists of two pictures Aand B, and that a difference between the pictures A and B is only themouth of the anchor person and the others are completely same. When apicture C, which is completely the same as the picture A is given and itis mechanically determined to which of the pictures A and B the pictureC is similar, if there is no coding distortion, a distance between thepicture C and the picture A is zero. On the other hand, regarding adistance between the picture C and the picture B, as a weight of a mouthportion with motion is large, the distance is sufficiently large. Now,considering that coding distortion exists in the background part of thepicture A, for example, although the distance between the picture C andthe picture A becomes large due to the coding distortion, as the weightof the background part with no motion is small, the distance between thepicture C and the picture A will never be larger than the distancebetween the picture C and the picture B.

Next, a third embodiment of the present invention will be described.

FIG. 13 shows an exemplary method of extracting features from a picture.In this method, pairs of any two regions within a picture are setbeforehand, and a difference between the features of the two regions ofa pair is obtained as a feature vector. In this embodiment, respectivepairs of regions are indicated as P1, P2, P3, . . . , and a featuredetermined from the n^(th) pair is indicated as Vn. Pairs of regions maytake various combinations of shapes and positions of regions, as shownin FIG. 13. Also, various methods can be used for calculating a featureVn from the pair Pn. For example, there is a method in which a meanvalue of luminance is calculated in each of a shaded region and areticulated region of a pair, and a value of the feature Vn isdetermined from the magnitude relation thereof. Specifically, a meanluminance value obtained within a reticulated region is subtracted froma mean luminance value obtained within a shaded region to calculate adifference, and when the difference is positive, Vn=1, while when thedifference is negative, Vn=−1. It is also possible that if the absolutevalue of the difference is smaller than a threshold, Vn is zero, so thatthe feature Vn is indicated by three values. It should be noted thatanother representative value can be used, instead of the mean luminancevalue. For example, a median value within a region or a valuecorresponding to the top a % of the luminance values in descending ordermay be used, or an amount showing the edge feature may be used as arepresentative value. For example, it is possible to apply a filter fordetecting an edge to a region, and perform statistical processing suchas averaging from the result to obtain a representative value.

The time axial direction change region extraction unit 100 calculates achange in the screen image in a time direction, with respect to eachregion formed by dividing it into MSN pieces (M and N represent naturalnumbers). For this calculation, Expressions 1 and 2 can be used. Aregion having a large amount of change in a time direction is selected,and an index of the region is output as change region information. Asmethods for selecting such a region, selecting a region when an amountof change in a time direction is not less than a given threshold, orselecting a given number of regions from the top when the regions arearranged in descending order of the amount of change, may be used.

It should be noted that if there are a large number of regions havinglarge amount of change, discrimination can often be made only using theentire picture. In that case, it is possible not to calculate a featurein a region unit. For example, if the number of regions having smallamount of change is not more than a certain threshold, a feature in aregion unit is not calculated. As such, nothing is output as changeregion information, or change region information may include informationshowing there is no feature extraction target region.

The obtained change region information is output to the each-regionfeature extraction unit 110. The each-region feature extraction unit 110extracts a feature of each region with respect to a region designated bythe change region information output from the time axial directionchange region extraction unit. As this feature, one similar to thatcalculated with respect to the entire picture can be used. As such, asshown in FIG. 13, any two regions within a picture are set as a pair,and a difference between the features of the pair of two regions isobtained as a feature vector. A method of setting a pair in this processand a method of calculating a representative value in a region may bethe same as those used for the entire picture, or different. Further, amethod of calculating a feature may be changed for each region.

As described above, even in a scene having less temporal change, it ispossible to construct features with which video segments can bediscriminated in a time axial direction with high accuracy.

While the embodiments of the present invention have been describedabove, the present invention is not limited to these examples. It willbe understood by those of ordinary skill in the art that various changesin form and details may be made therein without departing from the scopeof the present invention.

This application is based upon and claims the benefit of priority fromJapanese patent application No. 2009-12815, filed on Jan. 23, 2009, thedisclosure of which is incorporated herein in its entirety by reference.

INDUSTRIAL APPLICABILITY

The present invention is applicable to retrieval of similar or identicalvideos from various videos with high accuracy. In particular, regardingretrieval of the same segments of videos, the present invention isapplicable to identification of illegally copied moving imagesdistributed on the networks and identification of commercialsdistributed on actual airwaves.

REFERENCE NUMERALS

-   100 time axial direction change region extraction unit-   110 each-region feature extraction unit-   120, 620 multiplexing unit-   130, 630 each-picture feature extraction unit-   200, 210, 700, 710 demultiplexing unit-   220, 720 picture matching unit-   230 region matching unit-   240 matching result determination unit-   400 inter-picture difference calculation unit-   410 change region extraction unit-   500 motion information calculation unit-   510 change region extraction unit-   610 matching weight information extraction unit-   730 weighting coefficient calculation unit

1. A video signature extraction device, comprising: an each-picturefeature extraction unit that extracts a feature as an each-picturevisual feature from each picture which is a frame or a field of an inputvideo; a time axial direction change region extraction unit thatanalyzes an image change in a time direction with respect a plurality ofregions in the picture, obtains a region, among the plurality ofregions, having a large image change, and generates change regioninformation which is information designating the region; an each-regionfeature extraction unit that extracts a feature as an each-region visualfeature from the region corresponding to the change region information;and a multiplexing unit that generates a video signature which has theeach-picture visual feature, the each-region visual feature, and thechange region information.
 2. The video signature extraction device,according to claim 1, wherein the time axial direction change regionextraction unit calculates an inter-picture pixel value differencebetween the picture for which the change region information iscalculated and a previous or next picture, and calculates the changeregion information based on the inter-picture pixel value difference. 3.The video signature extraction device, according to claim 1, wherein thetime axial direction change region extraction unit performs motionestimation processing between the picture for which the change regioninformation is calculated and a previous or next picture, and calculatesthe change region information based on a degree of magnitude of anestimated motion.